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Software for the practical analysis of materials

Project description

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Spam is a piece of Python software built upon NumPy and SciPy for the analysis and manipulation of 3D and 2D data sets in material science, be they from x-ray tomography, random fields or any other source.

A number of common functions are provided that are either lacking or slow in Numpy and Scipy, which are expected to be used by users within new python scripts. These functions are in the tools/ directory, and include tools to work with random fields, morphological operations, digital image correlation, and labelled images. Some of spam’s functions transparently call C/C++ functions for speed.

Some user-callable scipts are also provided – they are more complex pieces of code that combine a number of functions and which have a command-line interface. For the moment the clients are 3 different image correlation techniques.

Please have a look at our online documentation for:

If you find bugs, need help, or want to talk to the developers, we use a riot/matrix.org chat room for organisation, please join it here and come and talk to us – it is easy, there is a chat client that can run in your web broswer. All you need to do is choose a user name!

Changelog

Version

Date

Notes

Version 0.5.1.2

2020-04-20

Fix and test for large initial guesses in register(), spam-mmr-graphical revived

Version 0.5.1.1

2020-04-08

Fix for running spam-ldic for pixel search

Version 0.5.1

2020-04-07

Fix for running spam-ddic with mpi, implementation of S. Brisard’s Directional Erosion

Version 0.5.0

2020-03-27

Big rename of scripts, functions, variables, parameters, with some backwards compatibility in TSV file reading. Some examples:

  • spam.correlate.lucasKanade -> spam.correlate.register

  • spam.helpers.readTSV -> spam.helpers.readCorrelationTSV

New framework for the calculation of strains, where the computation of F is separated from its decomposition. Output fields from correlation with prefixes “SubPix” and “SubPixel” become prefixless In TSV outputs from correlation the components like “F12” are now called “Fzy”

Version 0.4.3

2020-01-16

Various fixes to graphical clients (able to save TSV from spam-mmr-graphical and do a last, precise run with spam-mmr). Improvement to triangulation (now with CGAL alpha shapes) and discrete strain calculator (tested results)

Version 0.4.2

2019-09-25

spam-mmr-graphical now working, improvements in spam-mmr.

Version 0.4.1

2019-09-13

spam-mmr-graphical now working (c-python type error). Various bugfixes in clients. spam-ITKwatershed now accepts markers

Version 0.4.0

2019-07-18

c++ now bound with pybind11. New graphical script spam-mmr-graphical for multi-modal registration. New graphical script spam-ereg for eye (manual) registration. Python3 upgrade recommended for all users

Version 0.3.3.1

2019-05-27

Binning 2^31 fix, remove lines for immediate prints that are not py3 compatible First version with CGAL triangulation

Version 0.3.2.1

2019-05-14

Update pip documentation and changelog

Version 0.3.2

2019-04-30

Fix segfault with images larger than 2^31 voxels, and output both subtracted and original fields in spam-ldic

Version 0.3.1

2019-04-08

Fix a number of forgotten spam.DIC.transformationOperator functions

Version 0.3.0

2019-03-28

Consistent naming in DIC: Phi is 4x4 homogeneous deformation function and F is its internal 3x3 displacement gradient

Version 0.3.0

2019-03-28

Consistent naming in DIC: Phi is 4x4 homogeneous deformation function and F is its internal 3x3 displacement gradient

Version 0.2.2.2

2019-03-21

First version on pip with complete dependencies. This version of spam runs fully in a venv with pip install spam

Version 0.2.2.1

2019-03-20

Pull in requirements.txt into setup.py automatically. This aligns the build from git with the build from pip.

Version 0.2.2

2019-02-21

Approximate python3 compatibility

Version 0.2.1

2019-02-18

Add PyPI documentation to pip in RST

Version 0.2.0

2019-02-18

Add PyPI documentation to README.rst to appear on pip. Note that the build status and coverage badges won’t appear until access to gitlab is opened

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